Utilizing machine-learning based object detection to improve optical character recognition
US12288406B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 30, 2021 |
| Grant date | Apr 29, 2025 |
| Priority date | — |
| Expiry date | Mar 4, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V30/413
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately enhancing optical character recognition with a machine learning approach for determining words from reverse text, vertical text, and atypically-sized text. For example, the disclosed systems segment a digital image into text regions and non-text regions utilizing an object detection machine learning model. Within the text regions, the disclosed systems can determine reverse text glyphs, vertical text glyphs, and/or atypically-sized text glyphs utilizing an edge based adaptive binarization model. Additionally, the disclosed systems can utilize respective modification techniques to manipulate reverse text glyphs, vertical text glyphs, and/or atypically-sized glyphs for analysis by an optical character recognition model. The disclosed systems can further utilize an optical character recognition model to determine words from the modified versions of the reverse text glyphs, the vertical text glyphs, and/or the atypically-sized text glyphs.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.